class_docstr: Simply forward the list of input data.
  
  This is particularly useful when the Dataset contains textual data
  and in conjonction with the `Tuple` batchify function.
  
  Examples
  --------
  >>> import codel.data.batchify as bf
  >>> a = ([1, 2, 3, 4], "I am using MXNet")
  >>> b = ([5, 7, 2, 5], "Gluon rocks!")
  >>> c = ([1, 2, 3, 4], "Batchification!")
  >>> _, l = bf.Tuple(bf.Stack(), bf.List())([a, b, c])
  >>> l
  ['I am using MXNet', 'Gluon rocks!', 'Batchification!']
docstr: Parameters
  ----------
  data
      The list of samples
  
  Returns
  -------
  ret
      The input list
docstr_tok: ["Parameters","--","--","--","--","--","data","The","list","of","samples","Returns","--","--","--","-","ret","The","input","list"]
code: def __call__(self, data: t_List) -> t_List:
      """
      Parameters
      ----------
      data
          The list of samples
  
      Returns
      -------
      ret
          The input list
      """
      return list(data)
  
imports: import math
  from typing import AnyStr
  from typing import Callable
  from typing import Dict
  from typing import List
  from typing import NamedTuple
  from typing import Tuple
  from typing import Union
  import numpy
  import torch
  from ..utils import to_torch_dtype
label_desc: Use image node_id 1 for calling the List obj's underlying member method code with example usage: obj.__call__(data) and returns: list